lbo-model
FeaturedBuild leveraged buyout workbooks with IRR/MOIC in Excel.
AI & Automation 244,407 stars
50594 forks Updated today MIT
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Skill Content
## Environment
This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.
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## TEMPLATE REQUIREMENT
**This skill uses templates for LBO models. Always check for an attached template file first.**
Before starting any LBO model:
1. **If a template file is attached/provided**: Use that template's structure exactly - copy it and populate with the user's data
2. **If no template is attached**: Ask the user: *"Do you have a specific LBO template you'd like me to use? If not, I can use the standard template which includes Sources & Uses, Operating Model, Debt Schedule, and Returns Analysis."*
3. **If using the standard template**: Copy `examples/LBO_Model.xlsx` as your starting point and populate it with the user's assumptions
**IMPORTANT**: When a file like `LBO_Model.xlsx` is attached, you MUST use it as your template - do not build from scratch. Even if the template seems complex or has more features than needed, copy it and adapt it to the user's requirements. Never decide to "build from scratch" when a template is provided.
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## CRITICAL INSTRUCTIONS — READ FIRST
Use Python/openpyxl. Write formula strings (`ws["D20"] = "=B5*B6"`), then run the `excel-author` skill's `recalc.py` helper before delivery.
### Core Principles
* **Every cal...
Details
- Author
- NousResearch
- Repository
- NousResearch/hermes-agent
- Created
- 1 years ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
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